1 code implementation • 19 Jan 2022 • Geir Storvik, Alfonso Diz-Louis Palomares, Solveig Engebretsen, Gunnar Øyvind Isaksson Rø, Kenth Engø-Monsen, Aja Bråthen Kristoffersen, Birgitte Freiesleben de Blasio, Arnoldo Frigessi
During the first months, the Covid-19 pandemic has required most countries to implement complex sequences of non-pharmaceutical interventions, with the aim of controlling the transmission of the virus in the population.
1 code implementation • 5 Nov 2021 • Simen Eide, Arnoldo Frigessi, Helge Jenssen, David S. Leslie, Joakim Rishaug, Sofie Verrewaere
Although the usage of exposure data in recommender systems is growing, to our knowledge there is no open large-scale recommender systems dataset that includes the slates of items presented to the users at each interaction.
no code implementations • 2 May 2021 • Xiaoran Lai, Håkon A. Taskén, Torgeir Mo, Simon W. Funke, Arnoldo Frigessi, Marie E. Rognes, Alvaro Köhn-Luque
Coupling discrete cell-based models with continuous models using hybrid cellular automata is a powerful approach for mimicking biological complexity and describing the dynamical exchange of information across different scales.
2 code implementations • 30 Apr 2021 • Simen Eide, David S. Leslie, Arnoldo Frigessi
We introduce a variational Bayesian Recurrent Neural Net recommender system that acts on time series of interactions between the internet platform and the user, and which scales to real world industrial situations.
no code implementations • 31 Jul 2020 • Alvaro Köhn-Luque, Xiaoran Lai, Arnoldo Frigessi
Cancer pathology is unique to a given individual, and developing personalized diagnostic and treatment protocols are a primary concern.